8 Advance Python tricks you should know

8 Advance Python tricks 

In this article i will try to deliver you some cool tricks which you can use in your python code to make it more performant and simple.

Here are the 8 tricks, your code will definitely look  more technical.

1. Sorting Object by Multiple keys

Lets consider that we have to sorting the list of given dictionaries

people = [

{ 'name': 'ram', "age": 24 },

{ 'name': 'rohit', "age": 34 },

{ 'name': 'sam', "age": 26 },

{ 'name': 'ajit', "age": 54 },

{ 'name': 'amit', "age": 32 },

{ 'name': 'dom', "age": 34 },

{ 'name': 'brian', "age": 92 },

]

but the problem is we want to sort it by both name and age, not only by the name or age. In SQL we can do that by the code :  

SELECT * FROM people ORDER by name, age

In python there is a very simple solution present i.e sort function. Lets try this and check the output.

import operator

people.sort(key=operator.itemgetter('age'))

people.sort(key=operator.itemgetter('name'))

output :

[{'name': 'ajit', 'age': 54},
 {'name': 'amit', 'age': 32},
 {'name': 'brian', 'age': 92},
 {'name': 'dom', 'age': 34},
 {'name': 'ram', 'age': 24},
 {'name': 'rohit', 'age': 34},
 {'name': 'sam', 'age': 26}]

In this result you can see that names are sorted first then the age, if names are found sane then they will group together.

2. List Comprehension 

List comprehension removes all the complexities created due to for loops. Lets see the basic syntax fofr the list comprehension. 

[ expression for item in list if conditional ]

Now have a look in a very basic example

squares = []

for i in range(1,10):

    squares.append(i**2)

    print(squares)

output :

[1, 4, 9, 16, 25, 36, 49, 64, 81]

Now lets see an simple example

squares2 = [i**2 for i in range (1,11)]

print(squares2)

output :

[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

Negative no. of list by simple form

negative = []

for i in range (1,11):

    negative.append(-i)

    print(negative)

output :

[-1, -2, -3, -4, -5, -6, -7, -8, -9, -10]

An example with 'if' to filter the list 

filtered = [i for i in range(20) if i%2==0]

print(filtered)

output :

[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

3. Checking memory usage of an object

import sys

mylist = range(0, 2000)

print(sys.getsizeof(mylist))

output :

48

you should think that why this huge list only have 48 bytes

It’s because the range function returns a class that only behaves like a list. A range is a lot more memory efficient than using an actual list of numbers.

You can see for yourself by using a list comprehension to create an actual list of numbers from the same range:

import sys

myreallist = [x for x in range(0, 25000)]

print(sys.getsizeof(myreallist))

output :

200320

4. Data Classes

since version 3.7 of python offers the data classes.

There are several advantages over regular classes or other alternatives like returning multiple values or dictionaries:

• a data class requires a minimal amount of code
• you can compare data classes because __eq__ is implemented for you
• you can easily print a data class for debugging because __repr__ is implemented as well
• data classes require type hints, reduced the chances of bugs

from dataclasses import dataclass

@dataclass

class Card:

rank: str

suit: str

card = Card("Q", "hearts")

print(card == card)

# True

print(card.rank)

# 'Q'

print(card)

Card(rank='Q', suit='hearts')

5. The attrs Package

If you want more features or you are using an older version of python then you can use the attrs packages.

@attrs

class Person(object):

name = attrib(default='John')

surname = attrib(default='Doe')

age = attrib(init=False)

p = Person()

print(p)

p = Person('Bill', 'Gates')

p.age = 60

print(p)

output :

 Person(name='John', surname='Doe', age=NOTHING)
 Person(name='Bill', surname='Gates', age=60)

6. Merging two Dictionaries

dict1 = { 'a': 1, 'b': 2 }

dict2 = { 'b': 3, 'c': 4 }

merged = { **dict1, **dict2 }

print (merged)

output :

{'a': 1, 'b': 3, 'c': 4}

Note : here ** is used to unpack the dictionary

7. Find the Most Frequently Occurring Value

test = [1, 2, 3, 4, 2, 2, 3, 1, 4, 4, 4]

print(max(set(test), key = test.count))

output :

4

This code is working  because max() returns the highest value in the list

test.count is a built-in function of list. It takes an argument and will count the number of occurrences for that argument. 

set() returns all the unique values from test, so {1, 2, 3, 4}

8. Return Multiple Values

Functions in Python can return more than one variable without the need for a dictionary, a list, or a class. It works like this:

def get_user(id):

# fetch user from database

# ....

return name, birthdate

name, birthdate = get_user(4)

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